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Tidy a RREO tibble by topic, reconciling layout drift across years

Source: R/rreo_tidy.R
tidy_rreo.Rd

Filters a long RREO tibble (typically produced by get_rreo()) down to the rows that match a known indicator for topic (and optionally regime), using the rules in rreo_layout(). Account labels are matched on a year-stable, accent-folded key (Roman numerals and formula text are stripped before comparison), so the same call returns a coherent series across years even when SICONFI relabelled the appendix or account.

Usage

tidy_rreo(data, topic, regime = NULL)

Arguments

data

A tibble returned by get_rreo() or get_rreo_for_state(), with at least the columns exercicio, conta, coluna, valor.

topic

Character. Topic name (e.g., "previdencia"). See rreo_layout() for the supported set.

regime

Optional character. Filter to a subset of regimes within topic (e.g., "rgps", "rpps"). When NULL (default) all regimes are kept.

Value

A tibble with the matched rows, plus extra columns:

  • indicador: stable indicator name (e.g., "resultado_previdenciario_rgps").

  • regime: matched regime.

  • coluna_padrao, coluna_ano: see rreo_normalize_columns().

Details

Currently supported topics:

  • "previdencia" — federal previdência (RGPS, RPPS civis, FCDF, militares inativos) for the União sphere. Anexos 04.1 / 04.2 / 04.3 / 04.4 of the RREO; the layout knows that the RGPS appendix moved from 04.3 (up to 2022) to 04.4 (2023+) and that civis/FCDF moved from 04.1 (up to 2022) to 04.2 (2023+).

Pull requests adding new topics to inst/extdata/rreo_layout.csv are welcome.

See also

Other RREO tidy: rreo_layout(), rreo_normalize_columns()

Examples

if (FALSE) { # \dontrun{
library(dplyr)
rreo <- purrr::map_dfr(2019:2023, \(yr) {
  get_rreo(an_exercicio = yr, nr_periodo = 6,
           co_tipo_demonstrativo = "RREO",
           no_anexo = rreo_layout()$no_anexo[
             rreo_layout()$topic == "previdencia" &
             rreo_layout()$regime == "rgps" &
             yr >= rreo_layout()$first_year &
             yr <= rreo_layout()$last_year
           ][1],
           co_esfera = "U", id_ente = 1)
})
tidy_rreo(rreo, topic = "previdencia", regime = "rgps") |>
  filter(coluna_padrao == "DESPESAS LIQUIDADAS ATÉ O BIMESTRE",
         is.na(coluna_ano) | coluna_ano == exercicio) |>
  select(exercicio, indicador, valor)
} # }